摘要
为提高传统风险评估模型识别网络攻击的准确概率,笔者提出基于Web的网络信息安全风险评估模型研究,在计算风险因素的风险值、识别风险因素的脆弱性、处理原始数据信息矩阵的基础上,利用智能Web算法中的聚类法识别风险因素对网络信息的破坏程度、风险因素进行模块化的细化评估。对比实验得出,该模型识别攻击风险的准确率提高了2.2%。
In order to improve the accuracy of traditional risk assessment model to identify network attacks,the author proposes a webbased risk assessment model for network information security.Based on the calculation of risk value of risk factors,the identification of vulnerability of risk factors,and the processing of original data information matrix,the clustering method of Intelligent Web algorithm is used to identify the damage degree and risk factors of risk factors to network information Element to carry out modular refinement evaluation.The comparison experiment shows that the accuracy of the model to identify attack risk is improved by 2.2%.
作者
孔姝睿
赵艳
Kong Shurui;Zhao Yan(Shangqiu Institute of Technology,Shangqiu Henan 476000,China)
出处
《信息与电脑》
2020年第9期200-202,共3页
Information & Computer
关键词
WEB
信息安全
风险值
评估模型
Web
information security
risk value
evaluation model
